Classifications

• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
  • A61B5/4076—Diagnosing or monitoring particular conditions of the nervous system
  • A61B5/4094—Diagnosing or monitoring seizure diseases, e.g. epilepsy
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
  • A61B5/316—Modalities, i.e. specific diagnostic methods
  • A61B5/369—Electroencephalography [EEG]
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
  • A61B5/316—Modalities, i.e. specific diagnostic methods
  • A61B5/369—Electroencephalography [EEG]
  • A61B5/37—Intracranial electroencephalography [IC-EEG], e.g. electrocorticography [ECoG]
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
  • A61B5/316—Modalities, i.e. specific diagnostic methods
  • A61B5/369—Electroencephalography [EEG]
  • A61B5/372—Analysis of electroencephalograms

Definitions

• the present invention involves the field of signal processing. More particularly, the present invention involves the processing of electrical and/or electromagnetic signals generated by the brain.
• Epilepsy is a chronic disorder characterized by recurrent brain dysfunction caused by paroxysmal electrical discharges in the cerebral cortex. If untreated, an individual afflicted with epilepsy is likely to experience repeated seizures, which typically involve some level of impaired consciousness. Some forms of epilepsy can be successfully treated through medical therapy. However, medical therapy is less effective with other forms of epilepsy, including Temporal Lobe Epilepsy (TLE) and Frontal Lobe Epilepsy (FLE). With TLE and FLE, removing the portion of the hippocampus and/or cerebral cortex responsible for initiating the paroxysmal electrical discharges, known as the epileptogenic focus, is sometimes performed in an effort to control the seizures.
• TLE Temporal Lobe Epilepsy
• FLE Frontal Lobe Epilepsy
• seizure prediction will be understood to involve long-range forecasting of seizure-onset time
• seizure warning will be understood to involve long-range indications of conditions conducive to an impending seizure.
• any such technique would have numerous clinical as well as non-clinical applications.
• a technique might be used in conjunction with a device, perhaps an implanted device, designed to deliver a dosage of anti-seizure medication into the patient's bloodstream for the purpose of averting an impending seizure.
• such a technique could be used during pre-surgical evaluations to assist in pinpointing the epileptogenic focus, which is to be removed during surgery. It is understood that during a seizure, blood flow to the epileptogenic focus significantly increases. If certain radio-labeled ligands are injected into the patient's bloodstream in a timely manner, it is possible to monitor that increased blood flow using radiography, thereby allowing a physician to accurately pinpoint the boundaries of the epileptogenic focus.
• a true seizure prediction and/or warning technique would, ideally, provide an indication of an impending seizure well in advance so as to provide sufficient time to prepare for and administer, for example, the aforementioned radiography ligand.
• EEG electroencephalogram
• present techniques provide, with less than desirable accuracy, seizure detection during the very early stages of a seizure discharge in the EEG (i.e., a few seconds after the initial discharge) .
• the onset of the seizure discharge in the EEG may precede the clinical manifestations (e.g., behavioral and neuromotor responses) of the seizure by up to several seconds, particularly where intra-cranial electrodes are employed for EEG recordings.
• the EEG manifestation may be detected just a few seconds prior to the clinical manifestations of the seizure, some investigators have claimed the ability to predict seizures through evaluation of the EEG.
• seizure detection/warnings that precede seizure onset by 5, 10 or even 60 seconds are unlikely to offer any benefit because any medication administered at that time would not have time to reach a sufficient brain concentration to prevent an impending seizure.
• Even techniques that may be capable of detecting and/or generating seizure warnings no more than a few minutes prior to seizure onset may not support such a treatment.
• Each state space plot is used to derive correlation integrals for the corresponding signal, where the correlation integrals reflect the complexity (e.g., the correlation dimension, predictability indices) associated with the corresponding signal.
• a significant drop in the correlation integral values or the correlation dimension (i.e., a reduction in complexity) over time at specific brain sites can be used to trigger an impending seizure warning.
• J. Martinerie et al. "Epileptic Seizures can be Anticipated by Nonlinear Analysis”. Nature Medicine, vol. 4, pp. 1173-1176, 1998.
• CE. Elger et al. "Seizure Prediction by Nonlinear Time Series Analysis of Brain Electrical Activity.” European Journal of Neuroscience, vol. 10, pp. 786-789, 1998.
• the estimated measure of signal complexity is unreliable, as it depends on the brain state, and segments without epileptiform activity are arbitrarily selected as reference states. It also depends on which of numerous electrode sites are involved in estimating signal complexity. Furthermore, this technique provides no method for properly selecting brain sites. Also, the threshold used to trigger an impending seizure warning is arbitrary and not adaptive. Accordingly, this technique provides little if any practical utility.
• the non-linear techniques employed in the Hively patent can only detect and quantify changes in EEG or MEG signal dynamics that occur during the preictal transition period, just prior to seizure onset. The existence of these changes has been known for quite some time.
• L. lasemidis et al. "Non- Linear Dynamics of ECoG Data in Temporal Lobe Epilepsy" .
• spatio-temporal characteristics exhibited by certain sites within the brain when compared with the spatio-temporal, physiological characteristics exhibited by other sites within the brain, are noticeably different prior to an impending seizure as compared to the spatio-temporal characteristics exhibited by these sites during seizure free intervals.
• these spatio-temporal characteristics are noticeably different hours, and in some cases, days before the occurrence of a seizure.
• the present invention uses these differences as a seizure transition indicator for individual patients.
• the present invention involves a technique in which these critical, spatio-temporal characteristic changes are quantified for the purpose of providing impending seizure warnings (ISW), seizure susceptibility period detection (SSPD) hours or days before the impending seizure, and estimated time to impending seizure prediction (TISP).
• ISW impending seizure warnings
• SSPD seizure susceptibility period detection
• TISP estimated time to impending seizure prediction
• the present invention in contrast with the above-identified prior techniques, depends heavily on sequential estimates of the short-term largest Lyapunov exponent, which reflects a measure of chaoticity associated with the behavior of a corresponding electrode site.
• the present invention utilizes sequential comparisons of dynamic measures between two (2) or more electrode sites (i.e. , signal channels). Accordingly, it is an objective of the present invention to provide impending seizure warnings well in advance of seizure onset.
• the above- identified and other objects are achieved through a method of analyzing a multidimensional system.
• This method involves measuring each of a plurality of signals generated by the multidimensional system, where each of the plurality of signals represents a response associated with a corresponding spatial location within the multidimensional system.
• a phase space representation for each of the plurality of signals is then generated.
• a signal profile is derived for each of the plurality of signals, where each signal profile represents a level of chaoticity for each corresponding signal over time.
• Each of the signal profiles is then compared, and one or more groups of signals are selected, based on the comparison between their corresponding signal profiles.
• the state dynamics of the multidimensional system are characterized as a function of the signal profile comparisons associated with the selected one or more signal groups.
• the above- identified and other objects are achieved through a method which provides seizure warning and prediction.
• the method involves acquiring a time series signal from each of a plurality of locations about the brain, where each signal and its corresponding location constitute a corresponding channel. Then, for each channel, a spatio-temporal response is generated, based on the corresponding time series signal. The method then involves quantifying a sequence of chaoticity values for each channel based on the corresponding spatio-temporal response, where each sequence of chaoticity values constitutes a chaoticity profile. Over time, the chaoticity profiles associated with each of a number of channel pairs are compared, and the levels of entrainment between the chaoticity profiles associated with each of the channel pairs are evaluated.
• the above- identified and other objects are achieved through a method of activating a seizure interdiction device.
• This method involves acquiring each of a plurality of signals from a corresponding location of a patient's brain, where each signal constitutes a separate channel. Then, for each channel, a spatio-temporal response is generated, based on the corresponding signal. The method also involves generating a chaoticity profile, comprising a sequence of chaoticity values, for each channel based on the corresponding spatio-temporal response. Next, it is determined whether a level of entrainment between chaoticity profiles associated with a critical channel pair is statistically significant. If it is determined that the level of entrainment associated with the critical channel pair is statistically significant, a seizure warning is generated, and the seizure interdiction device is triggered to deliver an antiseizure treatment to the patient.
• the above- identified and other objects are achieved through an apparatus that provides seizure interdiction.
• the apparatus includes a plurality of sensors coupled to a patient's head, where the sensors detect signals from a corresponding location of the patient's brain.
• the apparatus also includes processing means for generating a seizure warning based on the plurality of signals detected by the plurality of sensors, where the processing means comprises: means for receiving the plurality of signals detected by the plurality of sensors; means for preprocessing the plurality of signals detected by the sensors so as to produce a digital equivalent for each of the signals; means for generating a spatio-temporal response for each of a corresponding one of the plurality of digital signals; means for generating a chaoticity profile, comprising a sequence of chaoticity values from each spatio- temporal response; means for determining whether a level of entrainment between chaoticity profiles associated with a critical pair of signals is statistically significant; and means for generating a seizure warning if it is determined that the level of entrainment associated with the critical signal pair is statistically significant.
• the apparatus includes a seizure interdiction device coupled to the above-identified processing means, where the seizure interdiction device comprises means for delivering an antiseizure treatment to the patient if a sei
• FIGS. 1(a) - (e) illustrates an exemplary, single channel EEG signal as a patient transitions through the various stages of an epileptic seizure
• FIG. 2 illustrates a typical, continuous multichannel EEG segment prior to and during seizure onset
• FIG. 3 is a flowchart depicting a procedure for providing early ISW, SSPD and TISP in accordance with exemplary embodiments of the present invention
• FIGS. 4 A and 4B illustrate the placement and use of different electrodes and electrode configurations
• FIGS. 5 A and 5B illustrate an EEG signal associated with a representative electrode channel over an epoch and the corresponding phase space portraits containing the attractor reconstructed generated from the EEG signal using the Method of Delays;
• FIG. 6 illustrates a procedure for calculating Lmax profiles for sequential epochs;
• FIG. 7 illustrates the Lmax profiles associated with each of a representative number of channel pairs
• FIG. 8 illustrates a procedure for comparing Lmax profiles (e.g. , estimations of T-index profiles) for the representative number of channel pairs shown in FIG. 7;
• FIG. 9 illustrates the Time to Impending Seizure (TIS) feature in accordance with exemplary embodiments of the present invention.
• FIGS. 10A and 10B illustrate the T-index profiles associated with two electrode pairs calculated over a 10-day period
• FIG. 11 illustrates an on-line system that incorporates the Impending Seizure Warning, Time to Impending Seizure and Seizure Susceptibility Determination features of the present invention.
• FIG. 12 illustrates a therapeutic intervention system that incorporates an indwelling device capable of providing Impending Seizure Warning, Time to
• FIGs. l(a-e) illustrate an exemplary electroencephalogram (EEG) signal, recorded from an electrode overlying an epileptogenic focus, as a patient transitions through the various stages of an epileptic seizure. More specifically, FIG. 1(a) illustrates a time sequence of the EEG signal during the preictal stage, which represents the period of time preceding seizure onset.
• FIG. 1(a) illustrates a time sequence of the EEG signal during the preictal stage, which represents the period of time preceding seizure onset.
• FIG. 1(b) illustrates a time sequence of the EEG signal during the transition period between the preictal stage and the ictal stage, that includes the seizure onset. It follows that FIG. 1(c) then reflects the EEG signal during the ictal stage, that is within the epileptic seizure, where the ictal stage begins at seizure onset and lasts until the seizure ends.
• FIG. 1(d) covers a transitional period. In this case, FIG. 1(d) illustrates a time sequence of the EEG signal during the transition from the ictal stage to the postictal stage, and includes the seizure's end.
• FIG. 1(e) then illustrates the EEG signal during the postictal stage, where the postictal stage covers the time period immediately following the end of the seizure.
• the preictal stage represents a period of time preceding seizure onset. More importantly, however, the preictal stage represents a time period during which the brain undergoes a dynamic transition from a state of spatio- temporal chaos to a state of spatial order and reduced temporal chaos .
• this dynamic transition during the preictal stage is characterized by dynamic entrainment of spatio-temporal responses associated with various cortical sites. More particularly, the dynamic entrainment of the spatio-temporal responses at these various cortical sites can be further characterized by:
• an EEG signal such as any of the EEG signals depicted in FIGs. l(a-e) is a time series that represents a temporal response associated with the spatio-temporal interactions of a particular portion of the brain where the corresponding electrode happens to be located.
• the brain is a complex, multidimensional system, EEG signals, and other known equivalents, do not and cannot visibly reflect the true spatio-temporal characteristics exhibited by the brain.
• traditional linear and nonlinear methods of processing EEG signals for the purpose of providing seizure prediction and/or warning have proven to be generally ineffective as the critical spatio-temporal characteristics exhibited by the brain during the preictal stage cannot be detected from EEG signals.
• these critical spatio-temporal characteristics exist long before seizure onset, in some cases, days before seizure onset. As such, these spatio-temporal characteristics exhibited by the brain during the preictal stage are essential to any true seizure prediction scheme.
• FIG. 2 shows a 20 second EEG segment covering the onset of a left temporal lobe seizure.
• the EEG segment of FIG. 2 was recorded referentially to linked ears from 12 bilaterally placed hippocampal depth electrodes (i.e., electrodes LDO1-LDO6 and RDO1- RDO6), 8 subdural temporal electrodes (i.e. , electrodes RST1-RST4 and LST1- LST4), and 8 subdural orbitofrontal electrodes (i.e., electrodes ROF1-ROF4 and LOF1-LOF4).
• hippocampal depth electrodes i.e., electrodes LDO1-LDO6 and RDO1- RDO6
• 8 subdural temporal electrodes i.e. , electrodes RST1-RST4 and LST1- LST4
• 8 subdural orbitofrontal electrodes i.e., electrodes ROF1-ROF4 and LOF1-LOF4
• Seizure onset begins approximately 1.5 seconds into the EEG segment as a series of high amplitude, sharp and slow wave complexes in the left depth electrodes, particularly in LDO1-LDO3, though most prominently in LDO2.
• the seizure spreads to right subdural temporal electrode RST1, and then to the right depth electrodes RDO1-RDO3.
• RST1-LDO3 right subdural temporal electrode
• RDO1-RDO3 right depth electrodes
• the present invention involves a technique that provides early, impending seizure warnings (ISW) .
• the present invention provides this early ISW by focusing on the afore-mentioned, critical spatio-temporal changes that occur during the preictal stage. Moreover, the present invention provides this capability even though the EEG would not manifest any indications of an impending seizure during the preictal stage, as illustrated in FIG. 2.
• the present invention is also capable of providing a seizure susceptibility period detection (SSPD), that is, the presence of abnormal brain activity long before the occurrence of a seizure, for example, during an interictal period days before a seizure.
• TISP time to impending seizure prediction
• the TISP reflects an amount of time that is expected to elapse before seizure onset.
• FIG. 3 is a flowchart that depicts a procedure for providing early ISW, SSPD, and TISP, in accordance with exemplary embodiments of the present invention.
• the procedure initially involves acquiring electrical or electromagnetic signals generated by the brain, in accordance with procedural step 305.
• Each of these signals may, for example, correspond to a single EEG channel, as one skilled in the art will readily appreciate.
• Each signal is then pre- processed, as shown in procedural step 310, where pre-processing typically includes signal amplification, filtering and digitization.
• Each of the digitized signals is then sampled, as illustrated in procedural step 315, so as to produce a set of successive samples (i.e., an epoch).
• the samples are used to generate a phase space portrait for each signal epoch.
• the rate of divergence of adjacent trajectories in the phase space is computed for each portrait, in accordance with procedural step 325, where the rate of divergence reflects the level of chaoticity associated with the corresponding signal.
• an average rate and standard deviation of divergence is periodically derived for each signal, in accordance with step 330, wherein each average rate of divergence value is based on numerous rate of divergence values within a "sliding" time window.
• the average rate of divergence values associated with each signal are then compared to the average rate of divergence values associated with each of the other signals, as shown in procedural step 335, using a statistical measure (e.g. T- index).
• a statistical measure e.g. T- index.
• a number of "critical” channel pairs may be identified, in accordance with procedural step 360, based on the average rate of divergence comparison accomplished, in accordance with procedural step 335, for each and every pair of signals.
• a critical channel pair is, in general, defined as a pair of signals that shows a relatively high degree of correlation (e.g., statistically significant low T-index values between their corresponding average rates of divergence), well before seizure onset.
• the initialization period is terminated, in accordance with the "NO" path out of decision step 340. Thereafter, the ISW, SSPD and TISP functions may be activated and the average rate of divergence comparisons associated with the critical channel pairs are used to generate an ISW, SSPD and/or TISP in a timely manner, in accordance with steps 350 and 355.
• procedural step 360 is accomplished during and after the initialization period. This step is a very important part of the present invention. It is based on observations that seizures are resetting mechanisms of the brain's spatio-temporal entrainment with the epileptogenic focus, which is the precursor of an impending seizure. See J.C. Sackellares et al. "Epileptic Seizures as Neural Resetting Mechanisms. " Epilepsia, vol. 38, p. 189, 1997.
• the reason it is important to continuously update the list of critical channel pairs, from one seizure to the next, even after the initialization period has ended (i.e., after the activation of the ISW, SSPD and TISP features) is that the brain does not necessarily reset itself completely after each seizure and, as a result, the spatio- temporal characteristics associated with any channel pair may be altered, a pair of signals previously identified as being a critical channel pair may have to be removed from the critical channel pair list, while a pair of signals that was not previously identified as being a critical channel pair may have to be added to the list of critical channel pairs to be used for a next ISW, SSPD or TISP.
• FIG. 3 is intended to illustrate a general procedure in accordance with exemplary embodiments of the present invention.
• the specific techniques, and alternatives thereto, used to implement each of the various procedural steps will now be described in greater detail herein below.
• procedural step 305 involves the acquisition of electrical or electromagnetic signals generated by the brain.
• electroencephalography is typically employed to record electrical potentials using electrodes, where two electrodes correspond to a separate channel, and where the recordings are made using differential amplifiers.
• one of the electrodes is common to all channels.
• the electrode pairs are strategically placed so that the signal associated with each channel is derived from a particular anatomical site in the brain. Electrode placement may include, for example, surface locations, where the electrodes are placed directly on a patient's scalp. Alternatively, subdural electrode arrays and/or depth electrodes are sometimes employed when it is necessary to obtain signals from intracranial locations. However, one skilled in the art will appreciate that the specific placement of the electrodes will depend upon the patient, as well as the application for which the signals are being recorded.
• FIG. 4A provides a view from the inferior aspect of the brain and exemplary locations for a number of depth and subdural electrodes.
• the electrodes include six right temporal depth (RTD) electrodes and six left temporal depth (LTD) electrodes located along the anterior-posterior plane in the hippocampi.
• FIG. 4A also includes four right orbitofrontal (ROF), four left orbitofrontal (LOF), four right subtemporal (RST) and four left subtemporal (LST) subdural electrodes located beneath the orbitofrontal and subtemporal cortical surfaces.
• FIG. 4B illustrates the placement of and use of a subdural electrode array as well as a strip of electrodes on the inferior right temporal lobe.
• magneto-electroencephalography may be employed to record the magnetic fields produced by the brain.
• MEG magneto-electroencephalography
• an array of sensors called superconducting quantum interference devices (SQUIDs) are used to detect and record the magnetic fields associated with the brain's internal current sources.
• micro-electrodes may be implanted into the brain to measure the field potentials associated with one or just a few neurons. It will be understood that the use of micro-electrodes might be advantageous in very select applications, where, for example, it might be necessary to define with a high degree of accuracy the location of the epileptogenic focus prior to a surgical procedure.
• the second procedural step 310 illustrated in FIG. 3 involves preprocessing the signals associated with each channel.
• This pre-processing step includes, for example, signal amplification, filtering and digitization.
• filters including a high pass filter with 0.1 to 1 Hz cutoff and a low pass filter with 70-200 Hz cutoff, are employed.
• other filters may be employed. For instance, if the signals are being recorded in the vicinity of power lines or any electrical fixtures or appliances operating on a 60 Hz cycle, a 60 Hz notch filter or time varying digital filters may be employed.
• the pre- processing step 310 results in the generation of a digital time series for each channel.
• Procedural step 320 involves generating phase portraits, and in particular, p-dimensional phase space portraits for each channel, where p represents the number of dimensions necessary to properly embed a brain state.
• the p-dimensional phase space portraits are generated as follows, where p is assumed to be at least seven (7) to capture the dynamic characteristics of the ictal state, which may be present during the preictal state.
• the digital signals associated with each channel are sampled over sequential time segments, referred to herein as epochs.
• Each epoch may range in duration from approximately 10 seconds to approximately 24 seconds, depending upon signal characteristics such as frequency content, amplitude, dynamic properties (e.g. , chaoticity or complexity) and stationarity. Generally, epoch length increases as stationarity increases.
• a signal may be sampled approximately 2000 times per epoch, where the epoch is approximately 10 seconds in duration.
• phase space portraits are constructed using the "Method of Delays.”
• the Method of Delays is well known in the art and, as stated above, a more detailed discussion of this method with respect to analyzing dynamic, nonlinear systems can be found in the Takens and Whitney publications, as well as lasemidis et al., "Phase Space Topography of the Electrocorticogram and the Lyapunov Exponent in Partial Seizures". Brain Topogr. , vol. 2, pp. 187-201 (1990).
• a phase space portrait is constructed using the Method of Delays by independently treating each unique sequence of p consecutive sample values, separated by a time delay ⁇ , as a point to be plotted in the p-dimensional phase space.
• ⁇ equals 4 samples (20 msec).
• FIG. 5A shows a 6 second epoch associated with an exemplary EEG signal at the onset of a seizure that originated in the left temporal cortex.
• FIG. 5B illustrates, from different perspectives, the corresponding phase space portrait, projected in three dimensions, for the exemplary EEG signal of FIG. 5A.
• the object appearing in the phase space portrait of FIG. 5B is called an "attractor" .
• the attractor represents the region within the phase space in which the states of the system evolve and remain confined thereto until the structure of the system changes.
• Procedural step 325 then involves quantifying the chaoticity of the attractor associated with each channel.
• the chaoticity of each attractor is quantified using Lyapunov exponents, which represents the average rate of divergence (i.e., expansion or contraction) between point pairs of trajectories that are in close proximity to one another in the phase space.
• Lyapunov exponents represents the average rate of divergence (i.e., expansion or contraction) between point pairs of trajectories that are in close proximity to one another in the phase space.
• the number of possible Lyapunov exponents is equal to the dimension (p) of the reconstructed state space. Therefore, quantifying the system's behavior may involve calculating sequences of one or more Lyapunov exponents.
• Lyapunov exponent sequences may be computed in quantifying the chaoticity of system's behavior.
• Lmax the largest Lyapunov exponent
• Lyapunov exponents it may be desirable to utilize more than one Lyapunov exponent (i.e. , Lyapunov exponents in addition to Lmax) in order to optimize sensitivity and specificity of seizure prediction.
• an Lmax value is ultimately derived for each epoch, thereby resulting in a sequence of Lmax values over time for each channel.
• This sequence of Lmax values (herein referred to as an Lmax profile) represents the chaoticity of the corresponding channel over time.
• each average Lmax value is derived based on a number of consecutive Lmax values that fall within a "sliding" time window, that may include several epochs, as illustrated in FIG. 6.
• the length of time associated with the time windows may, of course, vary. However, in accordance with a preferred embodiment of the present invention, the length of time associated with the "sliding" time windows is approximately 5 minutes (i.e., a span of approximately 30 epochs).
• procedural step 330 results in a sequence of average Lmax values over time for each channel.
• step 335 involves comparing the Lmax profile associated with each channel to the Lmax profile associated with each of the other channels, in order to determine whether the corresponding pair of signals show signs of entrainment.
• the term "entrain” refers to a correlation or convergence in amplitude and/or phase between two signals that make up a channel pair.
• a T-test is employed for this purpose in accordance with a preferred embodiment of the present invention.
• a T-index is derived for each of a number of overlapping or non-overlapping "sliding" time windows for each channel pair, wherein the duration of a time window may vary from approximately 1 minute to 20 minutes. As already mentioned, in a preferred embodiment of the present invention, the duration of these "sliding" time windows is approximately 5 minutes. Optimally, the length of time associated with these time windows must capture, with sufficient resolution, and a minimum number of computations, the dynamic spatio-temporal transitions during the preictal stage.
• the preictal transitions are characterized by the progressive entrainment of Lmax profile pairs (i.e., the Lmax profiles associated with each channel pair), it is the rate of entrainment between Lmax profile pairs and the level of statistical significance that determines the optimum length of these time windows.
• FIG. 7 illustrates a comparison between the Lmax profiles associated with each of a representative number of channel pairs. More particularly, FIG. 7 shows a comparison between the Lmax profile corresponding to a signal associated with a left temporal depth electrode LTD1 and the Lmax profiles associated with six other representative electrode sites.
• the six other representative electrode sites are a left orbitofrontal electrode LOF3, a right orbitofrontal electrode ROF3, a left subtemporal electrode LST4, a right subtemporal electrode RST4, a left temporal depth electrode LTD3 and a right temporal depth electrode RTD2.
• FIG. 7 only shows Lmax profile comparisons for six representative channel pairs, in a preferred embodiment of the present invention, procedural step 335 would typically involve Lmax profile comparisons associated with more than six channel pairs. For example, if signals are being recorded at 20 different electrode sites, procedural step 335 would typically involve 190 Lmax profile comparisons, as there are 190 different channel pairs.
• FIG. 8 illustrates the T-index profiles associated with the six channel pairs illustrated in FIG. 7. From the T-index profiles illustrated in FIG. 8, it is evident that the Lmax profiles associated with each of the six channel pairs all progressively become entrained during the preictal stage, while each channel pair becomes progressively disentrained during the postictal stage. However, the rate and degree to which the Lmax profiles become entrained and disentrained vary. In the example illustrated in FIG. 8, the channel pair associated with the electrode LTD1 and the electrode LTD3 demonstrates a relatively high level of entrainment (i.e. , relatively low T-index values), more so than the other five signal pairs.
• the channel pair associated with the electrode LTD1 and the electrode RTD2 also shows a relatively high level of entrainment, particularly during the preictal stage.
• FIG. 8 only shows T-index values 60 minutes prior to and 60 minutes following seizure onset, the preictal period typically begins approximately 15 minutes to as much as 2 hours prior to seizure onset.
• signs of entrainment such as reduced T-index values without statistical significance between certain signals, particularly those associated with critical channel pairs, may be evident long before seizure onset. In fact, it is possible that critical channel pairs will exhibit signs of an impending seizure days before an actual seizure.
• procedural steps 340, 345 and 360 involve the establishment of an initialization period, and thereafter, the update and/or maintenance of a library or list of critical channel pairs.
• a critical channel pair is defined as a pair of signals which together exhibit properties (e.g., entrainment) indicative of an impending seizure well in advance of other channel pairs, for example, the pair of signals associated with electrodes LTD1 and LTD3 illustrated in FIG. 7 and FIG. 8. Identifying certain channel pairs as critical channel pairs is, as illustrated in the flowchart of FIG.
• a post-seizure event that is based on the Lmax profile comparison data (i.e., the T index profiles) derived for each channel pair before, during and after a seizure.
• Lmax profile comparison data i.e., the T index profiles
• creating and maintaining the critical channel pair library is an iterative or adaptive process, in that, after each seizure, new channel pairs may be added to the critical channel pair library, while other channel pairs previously identified as being critical channel pairs, may be removed from the library.
• one to six seizures are required to create and refine the critical channel pair library during the initialization period.
• Refinement of the critical channel pair library is very important because, after the initialization period has ended, it is the behavior of the critical channel pairs that is analyzed in real-time in support of the ISW, SSPD and TISP features, in accordance with procedural step 350. Refinement of the critical channel pair library tends to reduce false positive detections, predictions and warnings.
• the specific techniques employed to generate an ISW, SSPD and/or TISP, in accordance with procedural step 355, will now be described in greater detail herein below. The first of these features to be described is the early ISW feature. In general, an ISW is triggered when one or more of the critical channel pairs become entrained for a statistically significant period of time.
• an ISW is generated when the average T index value associated with one or more critical channel pairs falls below a statistically significant threshold value for a statistically significant period of time.
• the statistically significant period of time during which the average T index value must remain below 2.09 in order to trigger an ISW is typically set somewhere between 15 minutes and 1.5 hours.
• a T index value less than 2.09 for a period of time equal to 15 minutes equates to a 99 percent confidence level that the issuance of an ISW is, in fact, a valid warning.
• the threshold value and the duration which the average T index must remain below that threshold may be adjusted to increase or decrease ISW sensitivity and reduce the incidence of false warnings (i.e. , false positives) for any given patient, or reduce the incidence of failed warnings (i.e. , false negatives).
• the ISW may be implemented in any number of ways.
• the ISW may involve audible warnings or visual warnings or a combination of both visual and audible warnings.
• the ISW may involve nothing more than the setting or resetting of an internal software variable or flag, wherein the setting or resetting of the variable or flag triggers a dependent event, such as the automatic delivery of anti-seizure medication. Accordingly, the specific implementation of the ISW will depend on the application for which the present invention is being employed.
• the rate of entrainment that is, the rate at which the Lmax profiles associated with a critical channel pair continue to converge, can be used to periodically estimate the amount of time before seizure onset. In accordance with a preferred embodiment of the present invention, this is accomplished by continuously deriving, for each of one or more critical channel pairs, the "slope" of the T-index profile over a "sliding" time window, as illustrated in FIG. 9.
• the point at which the slope intercepts the time (t) axis represents an estimated seizure onset time. Therefore, the difference between the present time and the estimated seizure onset time, along the time (t) axis, represents the TISP.
• the length of the "sliding" time window may, once again, vary. Initially, it may be set to a relatively small time interval (e.g., 15 minutes). Thereafter, it may be adaptively optimized for each individual patient.
• the last of the three features is the SSPD feature. Over a period of several hours, if not several days, prior to a seizure, or a first of a series of seizures, there is generally a gradual spatial entrainment among critical cortical sites. This gradual entrainment is thus exploited by the present invention to provide the SSPD feature. More specifically, the SSPD feature is, in accordance with a preferred embodiment of the present invention, implemented in much the same way as the ISW feature, that is, by generating a T-index profile for each of one or more critical channel pairs, and by observing those T-index profiles. However, the T- index profiles are typically generated and observed over a period of numerous hours or days, rather than a period of minutes. FIGs.
• 10A and 10B illustrate the T-index profiles associated with two electrode pairs calculated over a 10-day period.
• the patient was seizure-free during the first 135 hours of the recording. However, over the subsequent 90 hours, the patient experienced 24 seizures, as indicated by the 24 arrows located along the time (hours) axis.
• FIG. 10A shows the T-index profile associated with a focal electrode RTD3 and a contralateral subtemporal electrode LST4. For this electrode pair, dynamic entrainment occurred gradually, where the value of the T-indices fell below critical values only after the third day of recording. At the onset of seizures, resetting of entrainment occurs.
• the T-index profile associated with the bilateral hippocampal electrodes LTD3 and RTD3 falls below the statistically significant threshold value T c , approximately one (1) day into the recording, thus indicating that the signals associated with the electrode pair are entrained approximately four (4) days prior to the first seizure.
• the signals associated with this pair of electrodes remain mostly entrained until the first seizure, after which, the T-index profile values begin to reset progressively.
• the present invention exploits this behavior in order to provide the above-described SSPD feature. It should be noted that due to the time resolution (i.e., minutes) used for FIGS. 10A and 10B, resetting after each individual seizure cannot be visualized in these figures.
• the seizure warning and prediction technique illustrated in FIG. 3 relies on a comparison between two Lmax profiles for each of a number of channel pairs, where each Lmax profile is derived from a signal measured at a corresponding electrode site. More importantly, the seizure warning and prediction technique described above relies on a comparison of Lmax profiles for each of a number of critical channel pairs, where a critical channel pair has been defined as a pair of channels whose corresponding signals exhibit a relatively high degree of correlation with respect to one another, well before seizure onset. However, in some instances, seizure warning and seizure prediction may be improved by comparing the Lmax profiles associated with groups of three (3) or more channels (i.e., electrode site triplets, quadruplets, etc).
• T-index statistic i.e. , ANOVA statistic
• ANOVA statistic i.e. , ANOVA statistic
• neural network technology and pattern recognition techniques to analyze the level of entrainment between groups of two, three or more Lmax profiles.
• the physical implementation of the technique illustrated in FIG. 3 involves a combination of software, using standard programming techniques, hardware and/or firmware.
• the specific physical implementation will depend, to a large extent, on the application as illustrated herein below.
• FIG. 11 illustrates an on-line system 1100 that incorporates the various features of the present invention, as described above.
• the on-line system 1100 is primarily intended for use in any number of in-patient applications including diagnostic applications, as well as applications relating to patient treatment.
• the on-line system 1100 may be used to collect and process EEG or MEG signals for subsequent clinical interpretation (e.g., to analyze and determine seizure propagation patterns).
• the on-line system 1100 might also be used to alert hospital or clinic staff members of an impending seizure, via a local or telemetry link, so that staff members have adequate time to prevent patient injury or provide timely medical intervention to prevent the seizure itself; to observe the seizure; or to prepare for and administer other procedures that must be accomplished during the seizure, such as the administration of radiolabelled ligands or other substances required to obtain ictal SPECT, ictal FMRI, or ictal PET images for pre-surgical diagnostic purposes.
• pharmacological i.e., antiepileptic drug
• the currently accepted pharmacological approach is to prescribe fixed doses of one or more antiepileptic drugs (e.g. phenytoin, phenobarbital, carbamazepine, divalproex sodium, etc.) to be taken chronically at fixed time intervals.
• antiepileptic drugs e.g. phenytoin, phenobarbital, carbamazepine, divalproex sodium, etc.
• the objective is to achieve a steady-state concentration in the brain that is high enough to provide optimal seizure control, but low enough to reduce the risk of side-effects.
• FIG. 12 illustrates another alternative physical embodiment of the present invention. More particularly, FIG. 12 illustrates a pharmacological antiepileptic seizure system that includes an indwelling device, such as a real-time digital signal processing chip 1210, that contains, among other things, an algorithm that is capable of providing seizure warning and prediction (ASWP), in accordance with the present invention, as described above. As illustrated in FIG. 12, the ISW, TIS, and SSPD signals generated by the indwelling device 1210 are forwarded to a controller 1220.
• an indwelling device such as a real-time digital signal processing chip 1210
• ASWP seizure warning and prediction
• the controller 1220 can then trigger the release of a compound, such as a small dose of an anticonvulsant drug, into the blood stream of the patient, from a stimulator 1230 which contains or is connected to an indwelling reservoir 1230.
• a compound such as a small dose of an anticonvulsant drug
• the objective is to release a small quantity of anticonvulsant drug during the preictal transition stage to abort an impending seizure.
• FIG. 12 also illustrates that the therapeutic intervention system 1200 may, in addition to delivering anticonvulsant drug therapy, deliver electric or magnetic stimulation, for example, through a vagal nerve stimulator.
• Vagal nerve stimulators are currently used to deliver electrical impulses to the vagus nerve in the patient's neck at externally specified intervals, in an arbitrary fashion, with a specified duration and intensity.
• the present invention in accordance with the exemplary embodiment illustrated in FIG. 12, delivers an electrical impulse to the vagus nerve in the neck of specified duration and intensity, but the impulse is delivered only during the preictal transition state.
• the indwelling device 1210 detects the preictal transition state based on dynamical analysis of ongoing brain electrical activity, as described in detail above.
• vagal nerve stimulator When an impending seizure is detected, the indwelling vagal nerve stimulator is triggered and an electrical pulse is delivered to the vagus nerve in the neck. It will be readily apparent, however, to those skilled in the art that devices other than vagal nerve stimulators may be used in conjunction with the present invention.

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